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ARES POC

Research Verification Engine • Jan 2024

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Research IntegrityMathematicsVerification
A mathematically grounded misinformation verification engine using evidence aggregation metrics to ensure research integrity.

ARES (Automated Research Evidence Scorer) is a proof-of-concept for a new generation of integrity tools. It moves beyond simple plagiarism detection into the realm of logical and empirical verification.

The Formula

At the heart of ARES is a verification function: V(C) = f(R, S, N, W), where:

  • R: Replicability score
  • S: Source credibility
  • N: Network consensus
  • W: Weighting factor

System Logic

The system aggregates evidence from multiple scientific databases, weights them based on peer-review impact, and calculates a cumulative "Confidence Score" for specific claims.

Future of Verification

ARES demonstrates how algorithmic auditing can be applied to the sprawling ecosystem of digital research, providing a first line of defense against misinformation and hallucinated data in automated systems.

Core Capabilities

Multi-source evidence aggregation

Mathematical V(C) scoring logic

Real-time integrity verification

Evidence weighting & bias detection

Technical Stack

Python
Transformers
FastAPI
NLP
Evidence Scoring

Deployment

Production Ready

Architecture

Microservices / Edge